The detection of analytes such as nucleic acid sequences that are present in a biological sample has been used as a method for identifying and classifying microorganisms, diagnosing infectious diseases, detecting and characterizing genetic abnormalities, identifying genetic changes associated with cancer, studying genetic susceptibility to disease, and measuring response to various types of treatment. A common technique for detecting analytes such as nucleic acid sequences in a biological sample is nucleic acid sequencing.
Nucleic acid sequencing methodology has evolved significantly from the chemical degradation methods used by Maxam and Gilbert and the strand elongation methods used by Sanger. Today several sequencing methodologies are in use which allow for the parallel processing of thousands of nucleic acids all in a single sequencing run. The instrumentation that performs such methods is typically large and expensive since the current methods typically rely on large amounts of expensive reagents and multiple sets of optic filters to record nucleic acid incorporation into sequencing reactions.
It has become clear that the need for high-throughput, smaller, less expensive DNA sequencing technologies will be beneficial for reaping the rewards of genome sequencing. Personalized healthcare is moving toward the forefront and will benefit from such technologies; the sequencing of an individual's genome to identify potential mutations and abnormalities will be crucial in identifying if a person has a particular disease, followed by subsequent therapies tailored to that individual. To accommodate such an aggressive endeavor, sequencing should move forward and become amenable to high throughput technologies not only for its high throughput capabilities, but also in terms of ease of use, time and cost efficiencies, and clinician access to instruments and reagents.